LP1

1. LP1 Monitors LP4 LP3 LP2 Number of available monitors m; in the beginning assume one monitor present at every link. Sort links based on the traffic traversing them; least busy link goes on top. Pre- processing Phase Scan the list. Remove sequentially the monitors from the locations (links) that do not affect the global QoT estimation; the remainder should provide enough data to estimate accurately the end-to-end metric for all lightpaths. Stop when m monitored locations are left. Phase I Monitor No monitor Succeeded? Yes No Select the monitors that yield the least error in the global QoT estimation. Phase II Provide the solution (set of monitored locations). A Novel Monitor Placement Algorithm for Accurate Performance Monitoring in Optical Networks M. Angelou1,2, Y. Pointurier3, S. Azodolmolky1,2, D. Careglio1, S. Spadaro1 and I. Tomkos2 1Universitat Politècnica de Catalunya, C/ Jordi Girona, 1-3. 08034 Barcelona, Catalunya, Spain. 2Athens Information Technology, 19.5km Markopoulou Ave., 19002 Peania, Athens, Greece. 3Alcatel-Lucent, Bell Labs, Route de Villejust, 91620 Nozay, France. Abstract: We propose a novel monitor placement algorithm that reduces significantly thenumber of monitorsrequired to accurately assess the QoT of all lightpaths established in anoptical network, compared to other monitor placement methods. • Numerical Results • Compared PE with other monitor placement methods in a nation-wide backbone network with 46 unidirectional links • Assessed their performance through the relative rout mean square error (RMSE) • Given a specific placement solution, relative RMSE reflects the accuracy of the estimated values of the end-to-end performance metric (e.g. OSNR) of all lightpaths against the actual values. • QR uses an algebraic technique to place monitors1. • Busy Link utilizes an elementary technique that places m monitors at the m busiest links. • Solutions retrieved for 50 different traffic matrices assuming OSNR monitors and traffic load equal to 1 (corresponds to 1 demand per source-destination pair on average). Consider: Transparent optical network with no wavelength conversion. Issue: Monitoring QoT of all lightpaths requires one device per link  expensive Previous work: Possible to deploy a limited amount of physical devices and estimate QoT for lightpaths not physically monitored. Problem statement: Where to place the physicalmonitors to monitor the network's QoT as accurately as possible? Main Idea It is possible to use monitoring measurements collected from a subset of the network lightpaths(LP1, LP2, LP3) to estimateaccurately the corresponding end-to-end metric (e.g. OSNR) of the lightpaths that are not monitored (LP4). OSNR estimation is more accurate when monitors are placed with the PE heuristic. Placing only 15 monitors, that is 1/3 of the possible 46 locations, are enough to yield very low estimation error (2%). The OSNR of LP4 can be inferred as it shares links with the other monitored lightpaths (LP1, LP2, LP3) . The algorithm The Pseudo-Eye (PE) monitor placement algorithm is an efficient heuristic that returns the locations that maximize the accuracy of the QoT estimation of all the established connections and minimizes the required monitoring equipment. The estimation accuracy for PE and QR is not affected by the network load. Monitor Placement Solutions of PE for m = 15 and m = 20 monitors; 5 new monitors • Estimation Framework: Network Kriging (NK)1 • NK is a linear estimator • Applies to link-additive metrics (e.g. CD, OSNR, PMD, non-linear phase) • Note: hardware exists to monitor each of these metrics • PE uses NK to estimate the corresponding performance metric of “un-monitored” lightpaths based on the measurements from the monitors located in the other links An operator willing to upgrade its infrastructure will typically need to install additional monitors without changing the locations of the existing. Reference 1. D. B. Chua et al., IEEE J. Sel. Areas Commun. 24, 2263-2272 (2006). This work has been partly supported by the European Commission through the FP7 CHRON project and the Spanish Ministry of Science and Innovation through the DOMINO project (TEC2010-18522).